Italiano(IT) ProGVC: Progressive-based Generative Video Compression via Auto-Regressive Context Modeling

ProGVC框架通过自回归上下文建模推进生成视频压缩

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

研究人员推出了一种新颖的生成视频压缩框架ProGVC，该框架利用自回归上下文建模。该方法通过将视频编码为分层的多尺度残差令牌图，实现了渐进式传输和高效的熵编码。该系统通过传输粗到精的尺度子集来实现灵活的比特率适应，并且基于Transformer的上下文模型用于估计熵编码的令牌概率，以及在解码器处预测细尺度令牌以恢复感知细节。实验表明，ProGVC在低比特率下提供了有希望的感知压缩性能，同时保持了可扩展性。 AI

影响这一新框架可能带来更高效的视频压缩技术，影响流媒体服务和内容交付。

排序理由该条目是一篇研究论文，详细介绍了视频压缩的新技术框架。[lever_c_demoted from research: ic=1 ai=0.7]

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报道来源 [1]

arXiv cs.CV TIER_1 Italiano(IT) · Daowen Li, Ruixiao Dong, Kai Li, Ying Chen, Ding Ding, Li Li · 2026-09-01 04:00

ProGVC：基于渐进式生成视频压缩的自回归上下文建模

arXiv:2603.17546v2 Announce Type: replace Abstract: Perceptual video compression leverages generative priors to reconstruct realistic textures and motions at low bitrates. However, existing perceptual codecs often lack native support for variable bitrate and progressive delivery,…

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报道来源 [1]

ProGVC：基于渐进式生成视频压缩的自回归上下文建模

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